My book “AI and Machine Learning for On-Device Development: A Programmer’s Guide” is finally available
I’m delighted to announce that my latest book, “AI and Machine Learning for On-Device Development,” is now available.
AI and Machine Learning have been a passion of mine for some time – and I believe there’s a strong future for software developers who understand the shift to the new paradigm. I’ve made it my work at Google to make sure that getting into Machine Learning is as simple as possible so that we can lower the barriers of entry. Any developer can now get involved in the Machine Learning revolution. With this book, you’ll see how as an Android or an iOS developer, you can integrate Machine Learning models into your app.
I explore all the options available to you.
If you want the best of Google integrated into your app via turnkey off-the-shelf models, I’ll introduce how to do this using MLKit for both Android and iOS. Using this, you’ll get up and running quickly for everyday tasks like Image Recognition, Object Detection, and much more.
Should you want to customize the turnkey work, for example, to recognize specific images for which you have data, I show you how to do that instead of using the generic ones provided.
TensorFlow Lite is available for folks with custom model scenarios that go beyond the turnkey models.
When you build a TensorFlow model (see my other book for more details), you can optimize it for mobile using TensorFlow Lite. In this book, I’ll take you through that process, including integrating the model’s low-level Tensor interfaces into native high-level data types.
Often, if you want ML on your device, you won’t run the model on the device at all – and instead, execute it in the cloud!
I will step you through this scenario to deploy a model to the cloud using TensorFlow Serving and build a client app on Android or iOS that accesses it.
Full Table of Contents:
1: Introduction to AI and Machine Learning
2: Introduction to Computer Vision
3: Introduction to MLKit
4: Computer Vision Apps with MLKit on Android
5: Text Processing Apps with MLKit on Android
6: Computer Vision Apps with MLKit on iOS
7: Text Processing Apps with MLKit on iOS
8: Going Deeper: Understanding TensorFlow Lite
9: Creating Custom Models
10: Using Custom Models in Android
11: Using Custom Models in iOS
12: Productizing your app using Firebase
13: CreateML and CoreML for Simple iOS Apps
14: Accessing Cloud-Based Models from Mobile Apps
15: Ethics, Fairness, and Privacy for Mobile Apps